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 "cells": [
  {
   "cell_type": "markdown",
   "id": "ddfa9ae6-69fe-444a-b994-8c4c5970a7ec",
   "metadata": {},
   "source": [
    "# Project - Airline AI Assistant\n",
    "\n",
    "We'll now bring together what we've learned to make an AI Customer Support assistant for an Airline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b50bbe2-c0b1-49c3-9a5c-1ba7efa2bcb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports\n",
    "\n",
    "import os\n",
    "import json\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "747e8786-9da8-4342-b6c9-f5f69c2e22ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialization\n",
    "\n",
    "load_dotenv()\n",
    "\n",
    "openai_api_key = os.getenv('OPENAI_API_KEY')\n",
    "if openai_api_key:\n",
    "    print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
    "else:\n",
    "    print(\"OpenAI API Key not set\")\n",
    "    \n",
    "MODEL = \"gpt-4o-mini\"\n",
    "openai = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a521d84-d07c-49ab-a0df-d6451499ed97",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_message = \"You are a helpful assistant for an Airline called FlightAI. \"\n",
    "system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n",
    "system_message += \"Always be accurate. If you don't know the answer, say so.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61a2a15d-b559-4844-b377-6bd5cb4949f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This function looks rather simpler than the one from my video, because we're taking advantage of the latest Gradio updates\n",
    "\n",
    "def chat(message, history):\n",
    "    messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
    "    response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
    "    return response.choices[0].message.content\n",
    "\n",
    "gr.ChatInterface(fn=chat, type=\"messages\").launch()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36bedabf-a0a7-4985-ad8e-07ed6a55a3a4",
   "metadata": {},
   "source": [
    "## Tools\n",
    "\n",
    "Tools are an incredibly powerful feature provided by the frontier LLMs.\n",
    "\n",
    "With tools, you can write a function, and have the LLM call that function as part of its response.\n",
    "\n",
    "Sounds almost spooky.. we're giving it the power to run code on our machine?\n",
    "\n",
    "Well, kinda."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0696acb1-0b05-4dc2-80d5-771be04f1fb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's start by making a useful function\n",
    "\n",
    "ticket_prices = {\"london\": \"$799\", \"paris\": \"$899\", \"tokyo\": \"$1400\", \"berlin\": \"$499\"}\n",
    "\n",
    "def get_ticket_price(destination_city):\n",
    "    print(f\"Tool get_ticket_price called for {destination_city}\")\n",
    "    city = destination_city.lower()\n",
    "    return ticket_prices.get(city, \"Unknown\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80ca4e09-6287-4d3f-997d-fa6afbcf6c85",
   "metadata": {},
   "outputs": [],
   "source": [
    "get_ticket_price(\"London\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d20e3e2a-113d-446e-a4b5-93a7e2a7ae5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "weather = {\"london\": \"10 degree\", \"paris\": \"20 degree\", \"tokyo\": \"30 degree\", \"berlin\": \"15 degree\"}\n",
    "\n",
    "def get_weather(destination_city):\n",
    "    print(f\"Tool get_weather called for {destination_city}\")\n",
    "    city = destination_city.lower()\n",
    "    return weather.get(city, \"Unknown\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4afceded-7178-4c05-8fa6-9f2085e6a344",
   "metadata": {},
   "outputs": [],
   "source": [
    "# There's a particular dictionary structure that's required to describe our function:\n",
    "\n",
    "price_function = {\n",
    "    \"name\": \"get_ticket_price\",\n",
    "    \"description\": \"Get the price of a return ticket to the destination city. Call this whenever you need to know the ticket price, for example when a customer asks 'How much is a ticket to this city'\",\n",
    "    \"parameters\": {\n",
    "        \"type\": \"object\",\n",
    "        \"properties\": {\n",
    "            \"destination_city\": {\n",
    "                \"type\": \"string\",\n",
    "                \"description\": \"The city that the customer wants to travel to\",\n",
    "            },\n",
    "        },\n",
    "        \"required\": [\"destination_city\"],\n",
    "        \"additionalProperties\": False\n",
    "    }\n",
    "}\n",
    "\n",
    "weather_function = {\n",
    "    \"name\": \"get_weather\",\n",
    "    \"description\": \"Fetches the current weather for a given city. Call this whenever you need to know the weather. for example when a customer asks 'What's the weather like for this city'\",\n",
    "    \"parameters\": {\n",
    "      \"type\": \"object\",\n",
    "      \"properties\": {\n",
    "        \"destination_city\": {\n",
    "          \"type\": \"string\",\n",
    "          \"description\": \"The name of the city to get weather for.\"\n",
    "        }\n",
    "      },\n",
    "      \"required\": [\"destination_city\"],\n",
    "      \"additionalProperties\": False\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdca8679-935f-4e7f-97e6-e71a4d4f228c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# And this is included in a list of tools:\n",
    "\n",
    "tools = [{\"type\": \"function\", \"function\": price_function}, {\"type\": \"function\", \"function\": weather_function}]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0992986-ea09-4912-a076-8e5603ee631f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We have to write that function handle_tool_call:\n",
    "\n",
    "def handle_tool_call(message):\n",
    "    tool_responses = []\n",
    "    for tool_call in message.tool_calls:\n",
    "        function_name = tool_call.function.name\n",
    "        arguments = json.loads(tool_call.function.arguments)\n",
    "        city = arguments.get('destination_city')\n",
    "    \n",
    "        if function_name == \"get_ticket_price\":\n",
    "            result = get_ticket_price(city)\n",
    "        elif function_name == \"get_weather\":\n",
    "            result = get_weather(city)\n",
    "    \n",
    "        # Append tool response in OpenAI format\n",
    "        tool_responses.append({\n",
    "            \"role\": \"tool\",\n",
    "            \"tool_call_id\": tool_call.id,\n",
    "            \"name\": function_name,\n",
    "            \"content\": json.dumps(result)  # Convert result to JSON string\n",
    "        })\n",
    "    print(json.dumps(tool_responses, indent=2))\n",
    "    return tool_responses, city"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce9b0744-9c78-408d-b9df-9f6fd9ed78cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def chat(message, history):\n",
    "    messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
    "    response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
    "\n",
    "    if response.choices[0].finish_reason==\"tool_calls\":\n",
    "        message = response.choices[0].message\n",
    "        response, city = handle_tool_call(message)\n",
    "        messages.append(message)\n",
    "        # loop thru response\n",
    "        for res in response:\n",
    "            messages.append(res)\n",
    "        \n",
    "        response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
    "    \n",
    "    return response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3d3554f-b4e3-4ce7-af6f-68faa6dd2340",
   "metadata": {},
   "source": [
    "## With this implemenation, you can either ask for ticket price/weather separately or ask for both ticket and weather at the same time. \n",
    "    For example: I want to visit London, can you help me find ticket price and its weather\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4be8a71-b19e-4c2f-80df-f59ff2661f14",
   "metadata": {},
   "outputs": [],
   "source": [
    "gr.ChatInterface(fn=chat, type=\"messages\").launch()"
   ]
  }
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